Filtering combined dynamic stochastic resonance for enhancement of dark and low-contrast images

2017 ◽  
Author(s):  
Haijiao Liu ◽  
Jun Zhang
Keyword(s):  
Stochastic Resonance ◽  
Low Contrast ◽  
Dynamic Stochastic Resonance ◽  
Dynamic Stochastic

Enhancement of dark and low-contrast images using dynamic stochastic resonance

2013 ◽  
Vol 7 (2) ◽  
pp. 174-184 ◽  
Author(s):  
Rajlaxmi Chouhan ◽  
Rajib Kumar Jha ◽  
Prabir Kumar Biswas
Keyword(s):  
Stochastic Resonance ◽  
Low Contrast ◽  
Dynamic Stochastic Resonance ◽  
Dynamic Stochastic

scholarly journals Dark and low-contrast image enhancement using dynamic stochastic resonance in discrete cosine transform domain

2013 ◽  
Vol 2 ◽  
Author(s):  
Rajib Kumar Jha ◽  
Rajlaxmi Chouhan ◽  
Kiyoharu Aizawa ◽  
Prabir Kumar Biswas
Keyword(s):  
Stochastic Resonance ◽  
Discrete Cosine Transform ◽  
Enhancement Factor ◽  
Perceptual Quality ◽  
Cosine Transform ◽  
Low Contrast ◽  
Multi Scale ◽  
Dynamic Stochastic Resonance ◽  
Dynamic Stochastic ◽  
Color Enhancement

A novel technique based on dynamic stochastic resonance (DSR) in discrete cosine transform (DCT) domain has been proposed in this paper for the enhancement of dark as well as low-contrast images. In conventional DSR-based techniques, the performance of a system can be improved by addition of external noise. However, in the proposed DSR-based work, the intrinsic noise of an image has been utilized to create a noise-induced transition of a dark image to a state of good contrast. The proposed technique significantly enhances the image contrast and color information without losing any image or color data by optimization of bistable system parameters. The performance of the proposed methodology has been measured in terms of relative contrast enhancement factor, perceptual quality measure, and color enhancement factor. When compared with the existing enhancement techniques, such as adaptive histogram equalization, gamma correction, single-scale retinex, multi-scale retinex, modified high-pass filtering, multicontrast enhancement with dynamic range compression, color enhancement by scaling, edge-preserving multi-scale decomposition, automatic control of imaging tool, and various spatial/frequency-domain SR-based techniques, the proposed technique gives remarkable performance in terms of contrast and color enhancement while ascertaining good perceptual quality.

WATERMARK DETECTION USING DYNAMIC STOCHASTIC RESONANCE

2013 ◽  
Vol 12 (03) ◽  
pp. 1350010 ◽  
Author(s):  
RAJIB KUMAR JHA ◽  
APOORV CHATURVEDI ◽  
RAJLAXMI CHOUHAN
Keyword(s):  
Stochastic Resonance ◽  
Spread Spectrum ◽  
Internal Noise ◽  
External Noise ◽  
Detection Technique ◽  
Discrete Wavelet ◽  
Detection Techniques ◽  
Dynamic Stochastic Resonance ◽  
Watermark Embedding ◽  
Dynamic Stochastic

In this paper, a dynamic stochastic resonance (DSR) based watermark detection technique in discrete wavelet transform (DWT) domain is presented. Pseudo random bit sequence having certain seed value is considered as a watermark. Watermark embedding is done by embedding random bits in spread-spectrum fashion to the significant DWT coefficients. Watermark detection is quantitatively characterized by the value of correlation. The performance of watermark detection is improved by DSR which is an iterative process that utilizes the internal noise present in the image or external noise which is added during attacks. Even under various noise attacks, geometrical distortions, image enhancement and compression attacks, the DSR-based random bits detection is observed to give noteworthy improvement over existing watermark detection techniques. DSR-based technique is also found to give better detection performance when compared with the suprathreshold stochastic resonance-based detection technique.

Sign in / Sign up

Export Citation Format

Share Document